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  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

INTERNATIONAL JOURNAL OF INVENTIONS IN ENGINEERING & SCIENCE TECHNOLOGY

International Peer Reviewed (Refereed), Open Access Research Journal
(By Aryavart International University, India)

Paper Details

Enhancing The Efficiency Of Medical Imaging Diagnosis By Leveraging The Computer Vision In Conjunction With The Deep Learning Approach

Vanshika Goel

Vishwakarma University, Pune, Maharashtra, India

29 - 36 Vol. 9, Jan-Dec, 2023
Receiving Date: 2022-11-23;    Acceptance Date: 2023-01-19;    Publication Date: 2023-02-17
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Abstract

Typically, medical specialists examine how medical data is interpreted. Subjectivity and visual complexity limit the ability of a medical expert to comprehend images. The goal of this research is to determine whether using computer vision in medical imaging will be harmful to patients and what kind of obstacles we will have to overcome in order to use computer vision in healthcare, particularly medical imaging. This study aims to determine how well deep learning algorithms perform in disease classification based on medical imaging when compared to health-care professionals. Our approach in this study is a methodical review of the computer vision literature. The key to helping doctors maximize diagnosis accuracy in computer vision for medical imaging is the deep learning approach; it is safe and harmless to utilize to support medical imaging diagnosis.

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